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Record W4414207861 · doi:10.1192/j.eurpsy.2025.518

Good News? Assessing Time-Trends in Fidelity to Responsible Reporting of Suicide Guidelines in the Canadian News Media from 2019-2023

2025· article· en· W4414207861 on OpenAlexaffabout
Rob Whitley, Juliette Careau

Bibliographic record

VenueEuropean Psychiatry · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicRisk Perception and Management
Canadian institutionsDouglas Mental Health University InstituteDouglas CollegeMcGill University
Fundersnot available
KeywordsFidelityMental healthJournalismNews mediaSuicide preventionOccupational safety and healthContent analysisMedia coverage

Abstract

fetched live from OpenAlex

Introduction Research indicates that detailed and sensational media coverage of suicide can contribute to suicide mortality, known as the Werther Effect. Other research indicates that responsible reporting of suicide can promote hope and resilience, which can reduce suicidality, known as the Papageno effect. This has led to the development of responsible reporting of suicide guidelines. In Canada, these are contained in a booklet called Mindset, which was co-created by journalists and mental health experts. Mindset lists bullet-pointed recommendations for journalists, and has been widely disseminated to newsrooms, journalism schools and media professionals across the country, in tandem with educational activities aimed at journalists by suicide prevention experts. Objectives The overall aim of this study is to assess fidelity to Mindset responsible reporting of suicide guidelines in the Canadian media over a multi-year period. A secondary objective is to assess whether fidelity to responsible reporting of suicide guidelines during the COVID-19 pandemic was significantly different to pre/post pandemic reporting of suicide. Methods We collected articles from 47 different Canadian national and regional news sources mentioning the word suicide on a daily basis from April 1 st 2019 to March 31st 2023 (N=3,232). Each article was read and assessed for adherence to 12 key suicide reporting guidelines using a purposely-built coding sheet, derived from the Mindset guidelines. Trends in reporting were analyzed through time series analyses using a GLARMA model in R. software, including measuring for change during the COVID-19 pandemic. Results Significant increases in putatively protective content were observed over the four years, including rises in the inclusion of help-seeking information and the quotation of experts. Similarly, there was a general decrease in content that is putatively harmful, for example significantly fewer articles in latter years gave a monocausal explanation of suicide, used sensational language or described in detail any suicide method. That said, fewer than one-third of articles in the final year included educational content about suicide, help-seeking information, or quotes from suicide experts. Reporting of suicide during the COVID-19 pandemic showed some positive improvements compared to pre-pandemic reporting, but these were not sustained post-pandemic. Conclusions Fidelity to responsible reporting of suicide guidelines improved over the four-year period, especially recommendations concerning putatively helpful content. However there remains room for improvement regarding inclusion of putatively protective content such as including help-seeking information and educating the public about suicide. As such, further educational outreach to journalists is needed to encourage greater inclusion of protective content, while avoiding harmful content. Disclosure of Interest None Declared

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.565
Threshold uncertainty score0.408

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.065
GPT teacher head0.408
Teacher spread0.343 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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